Actionable companion · Assessment and evidence of learning

From evidence to district action: Generative AI adoption and its impact on teachers’ self-efficacy and instructional confidence in Ghana

AI-assisted editorial implementation guide. The district actions are proposed applications, not findings or recommendations attributed to the original authors. No additional peer review is asserted.

Evidence and context

Confirm the study population, setting and task before applying its findings to your district.

Original authors’ abstract, reproduced under the linked source license:

Background The rapid integration of Generative Artificial Intelligence (GenAI) into education presents unique opportunities and challenges, particularly in developing nations. While research has explored factors influencing GenAI adoption, its subsequent impact on teachers’ core professional beliefs remains under-investigated. This study addresses this gap by examining the relationship between GenAI usage and two critical psychological factors teacher self-efficacy (TSE) and instructional confidence among K-12 educators in Ghana. It further investigates the moderating role of institutional support and professional development. Methods An explanatory sequential mixed-methods design was employed. The quantitative phase involved a survey of 512 K-12 teachers from diverse districts in Ghana, utilizing validated scales to measure GenAI use, TSE (Teachers’ Sense of Efficacy Scale), instructional confidence, and perceived institutional support. Data were analyzed using descriptive statistics, correlation, and hierarchical multiple regression. The qualitative phase consisted of semi-structured interviews with a purposive sample of 20 teachers to provide deeper context and explanation for the quantitative findings. Results Quantitative analysis revealed a significant positive correlation between the frequency of GenAI use and both teacher self-efficacy (r = 0.42, p < 0.001) and instructional confidence (r = 0.48, p < 0.001). Hierarchical regression models indicated that using GenAI specifically for lesson planning and creating differentiated instructional materials were the strongest predictors of higher TSE. Furthermore, institutional support was found to be a significant moderator, amplifying the positive association between GenAI adoption and instructional confidence. Qualitative analysis corroborated these findings, yielding two primary themes: GenAI as an “Efficiency Engine,” which alleviates workload in resource-constrained settings, and GenAI as a “Creative Catalyst,” which enhances pedagogical innovation and design. Conclusion The findings suggest that the adoption of GenAI can serve as a potent tool for enhancing teacher self-efficacy and instructional confidence within the Ghanaian educational context. By automating routine tasks and providing novel pedagogical resources, GenAI empowers educators to focus on higher-order instructional strategies, thereby fostering greater professional competence. This effect is significantly strengthened when coupled with robust institutional support frameworks. This study offers critical insights for policymakers, school administrators, and teacher training institutions in Ghana and similar developing contexts, highlighting a strategic pathway for leveraging technology to empower the teaching workforce.

A 90-day district pilot

1. Days 1–15 · Appraise. Have the curriculum lead and a teacher read the methods and limitations. Record the study design, sample, comparator, outcomes and evidence gaps. Define a local question that the study can help inform.
2. Days 16–30 · Design. Redesign one low-stakes assessment: require a first attempt, an AI-assisted revision, a source-check log and a short oral explanation. Use the same rubric for the comparison task. Name an accountable owner and set the baseline, success threshold and budget before implementation.
3. Days 31–60 · Test. Start with a small voluntary cohort, preserve an accessible non-AI route and require teacher review. Use synthetic or de-identified examples; approve data handling and tool terms through district processes.
4. Days 61–90 · Decide. Blind-score reasoning, factual accuracy and unaided transfer on a fresh task. Record suspected misconduct separately from demonstrated evidence. Compare with baseline, document uncertainty and stop or revise if learning worsens, access is unequal or critical errors persist.

The board decision brief

Report the learning problem, evidence quality, participating population, total cost including review time, measured benefit, errors, access differences and remaining uncertainties. Make a dated recommendation to stop, revise or expand. A positive perception survey alone does not establish learning improvement.

Attribution and reuse

Emmanuel Nana Kwesi Ofori Darko; Zhanyong Qi; Zhiyuan Wang. Generative AI adoption and its impact on teachers’ self-efficacy and instructional confidence in Ghana. Frontiers in Artificial Intelligence (2026-06-18). https://doi.org/10.3389/frai.2026.1829056

Companion prepared 2026-10-30. Original authorship and DOI are preserved. The abstract is an attributed source extract; the implementation plan is new AI-assisted editorial material, offered under the same CC BY 4.0 license. This guide has not undergone independent peer review.